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app.py

@@ -81,12 +81,12 @@ def sales_price_batch():
     input_data = input_data.drop(['Product_Id', 'Store_Id', 'Store_Establishment_Year'], axis=1)
 
     # Apply same transformations
-    input_transformed = preprocessor.transform(input_data)
+    #input_transformed = preprocessor.transform(input_data)
 
     # Make predictions for all properties in the DataFrame (get log_prices)
-    predicted_sales = model.predict(input_transformed).tolist()
+    predicted_sales = model.predict(input_data).tolist()
 
-    # Calculate actual prices
+    # Calculate sales
     predicted_sales = round(float(predicted_sales), 2)
 
     # Create a dictionary of predictions with property IDs as keys